Working with molecular structures in pandas DataFrames
Molecular Processing Made Easy.
EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein
overview of datasets for ML in chemistry
Curses based ASCII molecule viewer for terminals.
Official implementation of All Atom Diffusion Transformers (ICML 2025)
Implementation of the Equiformer, SE3/E3 equivariant attention network that reaches new SOTA, and adopted for use by EquiFold for protein folding
Implementation of Torsional Diffusion for Molecular Conformer Generation (NeurIPS 2022)
Radient turns many data types (not just text) into vectors for similarity search, RAG, regression analysis, and more.
Tensorflow + Molecules = TensorMol
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
ScaffoldGraph is an open-source cheminformatics library, built using RDKit and NetworkX, for the generation and analysis of scaffold networks and scaffold trees.
A tensorflow.keras generative neural network for de novo drug design, first-authored in Nature Machine Intelligence while working at AstraZeneca.
Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.
A collection of resources for Deep Learning in Python for Life Sciences (with focus on biotech and pharma).
A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks
Geom3D: Geometric Modeling on 3D Structures, NeurIPS 2023
Graph convolutions in Keras with TensorFlow, PyTorch or Jax.
Python macromolecular parsing (with .pdb/.cif/.mmtf parsing and production)
🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics https://openreview.net/forum?id=SAT0KPA5UO
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